This works shows a comparison of two architectures of DBN (Deep Belief Networks) and a FFNN (Feed Forward Neural Network), stressing on understanding how DBNs work. Their robustness to noise and adversarial attacks is also tested.
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Comparison of DBNs and FFNN, stressing on understanding how DBNs work and how robust they are against noise and adversarial attacks.
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